Watkins, Dale (Health | 7 Mar 09:28 2013
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Re: IlluminaHumanMethylation450kprobe for nearest TSS calculation question

Thanks Tim, that makes perfect sense. Cheers Dale

________________________________________
From: Tim Triche, Jr. [tim.triche@...]
Sent: Thursday, 7 March 2013 5:19 PM
To: Dale Watkins [guest]
Cc: bioconductor@...; Watkins, Dale (Health)
Subject: Re: [BioC] IlluminaHumanMethylation450kprobe for nearest TSS calculation question

the other 65 probes are SNP probes, not CpGs or CpHs

On Wed, Mar 6, 2013 at 10:07 PM, Dale Watkins [guest]
<guest@...<mailto:guest@...>> wrote:

Hi,
I have been using the IlluminaHumanMethylation450kprobe reference manual to find the nearest TSS and
corresponding EntrezGene ID information for analysis of my 450k data, but I have a question.

The distance to TSS file I have generated contains 485512 rows, but the 450k array covers 485577 CpGs - why is
there a discrepancy? I used the code from the reference manual as follows:

# find the nearest TSS and its corresponding EntrezGene ID
library(GenomicFeatures)
CpGs.unstranded = CpGs.450k
strand(CpGs.unstranded) = "*"
refgene.TxDb = makeTranscriptDbFromUCSC("refGene", genome="hg19")
# nearest forward TSS
TSS.forward = transcripts(refgene.TxDb,
                          vals=list(tx_strand="+"),
                          columns="gene_id")
nearest.fwd = precede(CpGs.unstranded, TSS.forward)
nearest.fwd.eg<http://nearest.fwd.eg> = nearest.fwd # to keep dimensions right
notfound = which(is.na<http://is.na>(nearest.fwd)) # track for later
nearest.fwd.eg<http://nearest.fwd.eg>[-notfound] = as.character(elementMetadata(TSS.forward)$gene_id[nearest.fwd[-notfound]])

TSSs.fwd = start(TSS.forward[nearest.fwd[-notfound]])
distToTSS.fwd = nearest.fwd # to keep dimensions right
distToTSS.fwd[-notfound] = start(CpGs.unstranded)[-notfound] - TSSs.fwd
# note that these are NEGATIVE -- which is correct!

# nearest reverse TSS
TSS.reverse = transcripts(refgene.TxDb,
                          vals=list(tx_strand="-"),
                          columns="gene_id")
nearest.rev = precede(CpGs.unstranded, TSS.reverse)
nearest.rev.eg<http://nearest.rev.eg> = nearest.rev # to keep dimensions right
notfound = which(is.na<http://is.na>(nearest.rev)) # track for later
nearest.rev.eg<http://nearest.rev.eg>[-notfound] = as.character(elementMetadata(TSS.reverse)$gene_id[nearest.rev[-notfound]])

TSSs.rev = start(TSS.reverse[nearest.rev[-notfound]])
distToTSS.rev = nearest.rev # to keep dimensions right
distToTSS.rev[-notfound] = start(CpGs.unstranded)[-notfound] - TSSs.rev
# now these are POSITIVE: we are walking up the opposite strand.

# tabulate and link these together for the annotation package:
IlluminaHumanMethylation450kprobe$fwd.dist <- distToTSS.fwd
IlluminaHumanMethylation450kprobe$fwd.gene_id <- nearest.fwd.eg<http://nearest.fwd.eg>
IlluminaHumanMethylation450kprobe$rev.dist <- distToTSS.rev
IlluminaHumanMethylation450kprobe$rev.gene_id <- nearest.rev.eg<http://nearest.rev.eg>

FWD.CLOSER = with(IlluminaHumanMethylation450kprobe,
                  union( which( abs(fwd.dist) < abs(rev.dist) ),
                         which( is.na<http://is.na>(rev.dist) ) ) )
REV.CLOSER = with(IlluminaHumanMethylation450kprobe,
                  union( which( abs(fwd.dist) > abs(rev.dist) ),
                         which( is.na<http://is.na>(fwd.dist) ) ) )

IlluminaHumanMethylation450kprobe$DISTTOTSS =
pmin(abs(IlluminaHumanMethylation450kprobe$fwd.dist), abs(IlluminaHumanMethylation450kprobe$rev.dist))
IlluminaHumanMethylation450kprobe$ENTREZ = NA
IlluminaHumanMethylation450kprobe$ENTREZ[FWD.CLOSER] = IlluminaHumanMethylation450kprobe$fwd.gene_id
IlluminaHumanMethylation450kprobe$ENTREZ[REV.CLOSER] = IlluminaHumanMethylation450kprobe$rev.gene_id

write.table(IlluminaHumanMethylation450kprobe$DISTTOTSS, "DistToTSS.csv", sep=",")
write.table(IlluminaHumanMethylation450kprobe$ENTREZ, "ENTREZ.csv", sep=",")
write.table(IlluminaHumanMethylation450kprobe$ENTREZ[FWD.CLOSER], "Fwd.Closer.csv", sep=",")
write.table(IlluminaHumanMethylation450kprobe$ENTREZ[REV.CLOSER], "Rev.Closer.csv", sep=",")

Thanks in advance.

 -- output of sessionInfo():

R version 2.15.2 (2012-10-26)
Platform: x86_64-w64-mingw32/x64 (64-bit)

locale:
[1] LC_COLLATE=English_Australia.1252  LC_CTYPE=English_Australia.1252    LC_MONETARY=English_Australia.1252
[4] LC_NUMERIC=C                       LC_TIME=English_Australia.1252

attached base packages:
[1] parallel  stats     graphics  grDevices utils     datasets  methods   base

other attached packages:
 [1] SNPlocs.Hsapiens.dbSNP.20110815_0.99.6                 IlluminaHumanMethylation450kprobe_2.0.6
 [3] IlluminaHumanMethylation450kannotation.ilmn.v1.2_0.1.3 IlluminaHumanMethylation450k.db_1.4.7
 [5] org.Hs.eg.db_2.8.0                                     RSQLite_0.11.2
 [7] DBI_0.2-5                                              IlluminaHumanMethylation450kmanifest_0.4.0
 [9] BSgenome.Hsapiens.UCSC.hg19_1.3.19                     BSgenome_1.26.1
[11] GEOquery_2.24.1                                        GenomicFeatures_1.10.2
[13] AnnotationDbi_1.20.5                                   minfi_1.4.0
[15] Biostrings_2.26.3                                      GenomicRanges_1.10.7
[17] IRanges_1.16.6                                         reshape_0.8.4
[19] plyr_1.8                                               lattice_0.20-13
[21] Biobase_2.18.0                                         BiocGenerics_0.4.0
[23] BiocInstaller_1.8.3

loaded via a namespace (and not attached):
 [1] affyio_1.26.0         annotate_1.36.0       beanplot_1.1          biomaRt_2.14.0        bit_1.1-9
 [6] bitops_1.0-5          codetools_0.2-8       crlmm_1.16.9          ellipse_0.3-7         ff_2.2-10
[11] foreach_1.4.0         genefilter_1.40.0     grid_2.15.2           iterators_1.0.6       limma_3.14.4
[16] MASS_7.3-23           Matrix_1.0-11         matrixStats_0.6.2     mclust_4.0            multtest_2.14.0
[21] mvtnorm_0.9-9994      nor1mix_1.1-3         oligoClasses_1.20.0   preprocessCore_1.20.0 R.methodsS3_1.4.2
[26] RColorBrewer_1.0-5    RcppEigen_0.3.1.2.1   RCurl_1.95-3          Rsamtools_1.10.2      rtracklayer_1.18.2
[31] siggenes_1.32.0       splines_2.15.2        stats4_2.15.2         survival_2.36-14      tools_2.15.2
[36] XML_3.95-0.1          xtable_1.7-1          zlibbioc_1.4.0

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